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Using single‐cell genomics to understand developmental processes and cell fate decisions

High‐throughput ‐omics techniques have revolutionised biology, allowing for thorough and unbiased characterisation of the molecular states of biological systems. However, cellular decision‐making is inherently a unicellular process to which “bulk” ‐omics techniques are poorly suited, as they capture...

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Detalles Bibliográficos
Autores principales: Griffiths, Jonathan A, Scialdone, Antonio, Marioni, John C
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5900446/
https://www.ncbi.nlm.nih.gov/pubmed/29661792
http://dx.doi.org/10.15252/msb.20178046
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author Griffiths, Jonathan A
Scialdone, Antonio
Marioni, John C
author_facet Griffiths, Jonathan A
Scialdone, Antonio
Marioni, John C
author_sort Griffiths, Jonathan A
collection PubMed
description High‐throughput ‐omics techniques have revolutionised biology, allowing for thorough and unbiased characterisation of the molecular states of biological systems. However, cellular decision‐making is inherently a unicellular process to which “bulk” ‐omics techniques are poorly suited, as they capture ensemble averages of cell states. Recently developed single‐cell methods bridge this gap, allowing high‐throughput molecular surveys of individual cells. In this review, we cover core concepts of analysis of single‐cell gene expression data and highlight areas of developmental biology where single‐cell techniques have made important contributions. These include understanding of cell‐to‐cell heterogeneity, the tracing of differentiation pathways, quantification of gene expression from specific alleles, and the future directions of cell lineage tracing and spatial gene expression analysis.
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spelling pubmed-59004462018-04-23 Using single‐cell genomics to understand developmental processes and cell fate decisions Griffiths, Jonathan A Scialdone, Antonio Marioni, John C Mol Syst Biol Reviews High‐throughput ‐omics techniques have revolutionised biology, allowing for thorough and unbiased characterisation of the molecular states of biological systems. However, cellular decision‐making is inherently a unicellular process to which “bulk” ‐omics techniques are poorly suited, as they capture ensemble averages of cell states. Recently developed single‐cell methods bridge this gap, allowing high‐throughput molecular surveys of individual cells. In this review, we cover core concepts of analysis of single‐cell gene expression data and highlight areas of developmental biology where single‐cell techniques have made important contributions. These include understanding of cell‐to‐cell heterogeneity, the tracing of differentiation pathways, quantification of gene expression from specific alleles, and the future directions of cell lineage tracing and spatial gene expression analysis. John Wiley and Sons Inc. 2018-04-16 /pmc/articles/PMC5900446/ /pubmed/29661792 http://dx.doi.org/10.15252/msb.20178046 Text en © 2018 The Authors. Published under the terms of the CC BY 4.0 license This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Reviews
Griffiths, Jonathan A
Scialdone, Antonio
Marioni, John C
Using single‐cell genomics to understand developmental processes and cell fate decisions
title Using single‐cell genomics to understand developmental processes and cell fate decisions
title_full Using single‐cell genomics to understand developmental processes and cell fate decisions
title_fullStr Using single‐cell genomics to understand developmental processes and cell fate decisions
title_full_unstemmed Using single‐cell genomics to understand developmental processes and cell fate decisions
title_short Using single‐cell genomics to understand developmental processes and cell fate decisions
title_sort using single‐cell genomics to understand developmental processes and cell fate decisions
topic Reviews
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5900446/
https://www.ncbi.nlm.nih.gov/pubmed/29661792
http://dx.doi.org/10.15252/msb.20178046
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